Automatic Vehicle Route Prediction based on Multi-Sensor Fusion

To solve the problem of inaccurate results of vehicle routing prediction caused by a large number of uncertain information collected by different sensors in previous automatic vehicle route prediction algorithms, an automatic vehicle route prediction algorithm based on multi-sensor fusion is studied. The process of fusion of multi-sensor information based on the D-S evidence reasoning fusion algorithm is applied to automatic vehicle route prediction. According to the contribution of a longitudinal acceleration sensor and yaw angular velocity sensor detection information to the corresponding motion model, the basic probability assignment function of each vehicle motion model is obtained; the basic probability assignment function of each motion model is synthesized by using D-S evidence reasoning synthesis formula. The new probability allocation of each motion model is obtained under all evidence and then deduced according to the decision rules. Guided by the current optimal motion model, the optimal motion model at each time is used to accurately predict the vehicle movement route. The simulation results show that the prediction error of the algorithm is less than 4% in the process of 30 minutes of automatic vehicle route prediction.

Analysis of Biodiesel Spray Combustion in Internal-Combustion Engine using Multidimensional Models

With the rapid scale expansion of the first generation of bio-liquid fuels, its impact on the prices of agricultural products, food security and the environment has begun to emerge and attracted extensive attention from governments and academia. A new multi-dimensional model of biodiesel spray combustion in an internal combustion (IC) engine is designed. Firstly, the BP neural network mining model is used to extract the spray combustion data of the IC engine. Then, based on the combustion data of biodiesel load in an internal combustion engine, burning rate and heat release, the principle of spray combustion of biodiesel is analyzed. Finally, from the two aspects of gas-phase control and liquid phase control, a multi-dimensional model of biodiesel spray combustion in IC engine is established and the spray combustion characteristics of biodiesel in IC engine are analyzed. The research results show that the model can effectively analyze the effect of load and fuel temperature on the spray combustion characteristics of biodiesel and the results of the model are almost the same as the actual data and the calculation accuracy is high. It is an effective method for studying the spray combustion characteristics of biodiesel.

Clustering Algorithm for Vehicle’s Driving Data Feature based on Integrated Navigation

The clustering result of K-means clustering algorithm is affected by the initial clustering center and the clustering result is not always global optimal. Therefore, the clustering analysis of vehicle’s driving data feature based on integrated navigation is carried out based on global K-means clustering algorithm. The vehicle mathematical model based on GPS/DR integrated navigation is constructed and the vehicle’s driving data based on GPS/DR integrated navigation, such as vehicle acceleration, are collected. After extracting the vehicle’s driving data features, the feature parameters of vehicle’s driving data are dimensionally reduced based on kernel principal component analysis to reduce the redundancy of feature parameters. The global K-means clustering algorithm converts clustering problem into a series of sub-cluster clustering problems. At the end of each iteration, an incremental method is used to select the next cluster of optimal initial centers. After determining the optimal clustering number, the feature clustering of vehicle’s driving data is completed. The experimental results show that the global K-means clustering algorithm has a clustering error of only 1.37% for vehicle’s driving data features and achieves high precision clustering for vehicle’s driving data features.

Vehicle Body and Roll Cage Assessment involving Frontal, Side and Roll-over Crash Analysis by FEA using LS-Dyna

Simulating the vehicle collision has gained importance in the automotive sector due to its accuracy, cost effectiveness and enhanced reliability. It aids in improving the safety of driver and passenger and also examine the cause of crash or collision. This numerical analysis investigates the materials capability to enhance safety. A three-dimensional vehicle model was developed along with its roll cage using solid work tool. Hypermesh work bench was employed to discretise the sensitive parts of the body and roll cage using beam 189 element having six degree of freedom at each node. The existing structural steel members were replaced with reinforced carbon fibre in all the sensitive part of the body and roll cage and its structural stability was assessed using the frontal, side and roll over crash simulation using LS Dyna. This investigation also reveals the change in internal energy, kinetic energy absorption and momentum transfer for both structural steel and carbon fiber under all the crash scenarios. The outcomes of this numerical investigation proved that the reinforced carbon fiber can be effectively replaced with the structural steel to enhance safety.

Application of TOPSIS Method for Prediction of Optimum Design Parameters of Micro Hole Textured Cutting Inserts in Turning of Al-MMC

Metal Matrix Composite (MMC) has better mechanical properties and it is possible to produce near net shape. Aluminum-based MMC (Al-MMC) has challenges in terms of machinability studies and estimation of its optimum process parameters. Alternative cutting fluid research is a challenging area in machining. To avoid, existing hydrocarbon oil-based cutting fluid, textured inserts embedded with a solid lubricant are one of the alternative solutions. Micro hole textured inserts make a hole on the rake face of the cutting tool inserts. Texture includes various important design parameters namely hole diameter, hole depth and pitch between the holes. These optimum parameters influence the machining process. In this work, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used to find the optimum design parameters (hole diameter, hole depth and pitch between holes) during turning of Al- MMC. The objective parameters considered are minimization of surface roughness, power consumption and tool flank wear. The optimum combination of these design parameters is obtained by the higher relative closeness value of the TOPSIS method. The result of the investigation revealed that these design parameters are important to obtain improved machining performance. Also, it is understood that the TOPSIS method has an appropriate procedure to solve multiple objective optimization problems in manufacturing industries.

Combustion and Emission Characteristics of Dual Fuel Engine for Different Parameters

The effects of compression ratio and fuel delivery advance angle on the combustion and emission characteristics of premixed methanol charge induced ignition by Fischer Tropsch diesel engine were investigated using a CY25TQ diesel engine. In the process of reducing the compression ratio from 16.9 to 15.4, the starting point of combustion is fluctuating, the peak of in-cylinder pressure and the maximum pressure increase rate decrease by 44.5% and 37.7% respectively. The peak instantaneous heat release rate increases by 54.4%. HC and CO emissions are on a rising trend. NOx and soot emissions were greatly decreased. The soot emission has the biggest drop of 50%. Reducing the fuel delivery advance angle will make the peak of in-cylinder pressure and the peak of pressure rise rate increase while the peak of heat release rate decreases. The soot emission is negatively correlated with the fuel delivery advance angle. When the fuel delivery advance angle is 16° CA, the soot emissions increased the most by 130%.

Microstructural, Thermal and Corrosion Characterization of Friction Stir Welded Magnesium Alloys

The requirement for structural materials with demanding properties is always a major concern among automotive researchers. Magnesium alloys possess the required properties. In this work magnesium alloys, AZ31B and AZ91B were joined by friction stir welding. The influence of process parameters on the weld properties has been studied. The process parameters were tool rotational speed, welding speed, tilt angle. Three different combinations AZ31B-AZ91B, AZ31B-AZ31B and AZ91B-AZ91B were friction stir welded. Non-destructive tests have been performed on the welded joints as the primary analysis. After mechanical testing, optical microscopic examination comprising of macrostructure analysis, microstructure analysis and SEM analysis were carried out on selected specimens and the results are formulated. The corrosion behavior of Mg alloys has been tested using a salt spray test. The thermal behavior was studied using thermogravimetric and differential thermal analysis. The joints were friction stir welded with maximum efficiency where grain refinement was observed in the weld microstructure of dissimilar alloys and the elongated grains was recrystallized. This paper primarily focuses on the microstructural aspects, corrosion performances and TG/DTA analysis.

Micro Textured Cutting Inserts with Solid Lubrication as Alternative Coolant to Mineral Oil-Based Cutting Fluid in Turning Operation

Turning process is a primary process in engineering industries and optimization of process parameters enhance the machining performance. Inconel 718 is a nickel-based superalloy, widely found applications in the manufacturing of blades, sheets and discs in aircraft engines and rocket engines. It provides toughness at low temperature, with stand high mechanical stresses at elevated temperature and creep resistance. In this work, turning process is carried out on Inconel 718 with micro whole textured cutting inserts filled with solid lubricants. Three different solid lubricants are used namely molybdenum-di-sulfide (MoS2), tungsten-di-sulfide (WS2) and calcium-di-fluoride (CaF2). Experiments are performed as per L9 orthogonal array. Statistical approaches such as orthogonal array, Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA) are used to find the importance and effects of machining parameters. In this study, input parameters included are feed, cutting speed and depth of cut and output parameter includes surface roughness. Optimization of process parameters is carried out and the significance is estimated. The result suggested that WS2 followed by MoS2 and CaF2 given good surface finish value. Also, solid lubricant in machining enhances the sustainability in manufacturing.

Multi Response Optimization of Process Parameters using Taguchi based Grey Relational Method in FSW of AZ91B Magnesium Alloy

In this paper, the Taguchi method and grey relational analysis have been used to evaluate the weldability of AZ91B Magnesium alloy by friction stir welding process. Experiments were conducted using the L9 Taguchi design considering an orthogonal array consist of 3 factors and 3 levels. The rotational speed, transverse speed and angle of tilt of the tool are selected as welding parameters. Analysis of variance (ANOVA) is used to analyze the influence of the welding parameters on the responses namely, ultimate tensile strength (UTS) and hardness. The analysis results revealed that the transverse speed is the predominant parameter affecting tensile strength, hardness and quality of the weld. Confirmation test results showed that the Taguchi method coupled with grey relational analysis is very successful in the optimization of welding parameters for maximum strength and hardness in the FSW of AZ91B Magnesium alloy.

A Survey on Internet of Vehicles Applications, Architecture, Communication Models and Challenges

To solve the problems of long shifting time and low transmission efficiency of motor transmission in unmanned electric vehicles, the performance test of motor transmission is carried out. The EMT transmission system is selected as the test object of the motor transmission of an unmanned electric vehicle. The gear number of the transmission is determined with the aim of reducing the speed requirement of the motor when the motor runs at high speed and working in the high-efficiency area near the base speed as far as possible. According to the gear speed and torque of the load motor, the driving moment and torsion moment of the drive motor in the acceleration stage are determined based on the total inertia of the drive motor and other parameters. Finally, the test bench of the motor transmission towing is set up and the test is carried out. The experimental results show that when the rated torque of the motor transmission is 100% at 1600r/min shift speed point and 150% at 1800r/min shift speed point, the minimum shift time of the motor transmission is 425ms. Meanwhile, the transmission efficiency of the motor transmission of the unmanned electric vehicle is between 90% and 92% and the transmission performance is high.